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Intercomparison of aerosol optical depths from four reanalyses and their...

Xian, P., J. S. Reid, M. Ades, A. Benedetti, P. R. Colarco, A. da Silva, T. F. Eck, J. Flemming, E. Hyer, Z. Kipling, S. Rémy, T. Sekiyama, T. Tanaka, K. Yumimoto, and J. Zhang (2024), Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus, Atmos. Chem. Phys., doi:10.5194/acp-24-6385-2024.
Abstract: 

The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of aerosol optical depth (AOD) trends and attribution over multi-decadal timescales. Notable multi-year aerosol reanalyses currently available include NAAPS-RA from the US Naval Research Laboratory, the NASA MERRA-2, JRAero from the Japan Meteorological Agency (JMA), and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, as well as data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where divergence and challenges are prominent. Regions with high pollution and often mixed fine-mode and coarse-mode aerosol environments, such as South Asia, East Asia, Southeast Asia, and the Maritime Continent, pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions and remote oceans, exhibit large relative differences in speciated AODs and fine-mode versus coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis consensus (MRC, i.e., ensemble mean) approach was developed similarly to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAPMME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments.

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Research Program: 
Interdisciplinary Science Program (IDS)
Funding Sources: 
80NSSC20K1260